Triple

T35027948
Position Surface form Disambiguated ID Type / Status
Subject Bronte Park E1010393 entity
Predicate locatedIn P40 FINISHED
Object Bronte, New South Wales
Bronte, New South Wales is a coastal suburb of Sydney, Australia, known for its popular beach, ocean baths, and scenic coastal walk.
E2123411 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Bronte, New South Wales | Statement: [Bronte Park, locatedIn, Bronte, New South Wales]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bronte, New South Wales
Triple: [Bronte Park, locatedIn, Bronte, New South Wales]
Generated description
Bronte, New South Wales is a coastal suburb of Sydney, Australia, known for its popular beach, ocean baths, and scenic coastal walk.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f76dccf0108190af43b465d3750196 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7854441e081908c6066125c3ba574 completed May 3, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37c62d53b08190b088557b491bf493 completed June 21, 2026, 11:08 a.m.
NEDg Description generation batch_6a37c6a375b08190a4fed21a96ca40d3 completed June 21, 2026, 11:10 a.m.
NED2 Entity disambiguation (via description) batch_6a37c73c47b08190a691c8afb098a9f3 completed June 21, 2026, 11:13 a.m.
Created at: May 3, 2026, 4:01 p.m.